ROBERT L ROTH
Optometry in Newton, MA

4837831, Jun 6, 1989

Oct 15, 1986

6/919885

Laurence Gillick - Brookline MA
Paul G. Bamberg - Framingham MA
James K. Baker - West Newton MA
Robert S. Roth - Newtonville MA

Dragon Systems, Inc. - Newton MA

G10L 500

381 43

A first speech recognition method receives an acoustic description of an utterance to be recognized and scores a portion of that description against each of a plurality of cluster models representing similar sounds from different words. The resulting score for each cluster is used to calculate a word score for each word represented by that cluster. Preferably these word scores are used to prefilter vocabulary words, and the description of the utterance includes a succession of acoustic decriptions which are compared by linear time alignment against a succession of acoustic models. A second speech recognition method is also provided which matches an acoustic model with each of a succession of acoustic descriptions of an utterance to be recognized. Each of these models has a probability score for each vocabulary word. The probability scores for each word associated with the matching acoustic models are combined to form a total score for that word.

4805218, Feb 14, 1989

Apr 3, 1987

7/034842

Paul G. Bamberg - Framingham MA
James K. Baker - West Newton MA
Laurence Gillick - Newton MA
Robert S. Roth - Newtonville MA

Dragon Systems, Inc. - Newton MA

G10L 100

381 43

A method of speech analysis calculates one or more difference parameters for each of a sequence of acoustic frames, where each difference parameter is a function of the difference between an acoustic parameter in one frame and an acoustic parameter in a nearby frame. The method is used in speech recognition which compares the difference parameters of each frame against acoustic models representing speech units, where each speech-unit model has a model of the difference parameters associated with the frames of its speech unit. The difference parameters can be slope parameters or energy difference parameters. Slope parameters are derived by finding the difference between the energy of a given spectral parameter of a given frame and the energy, in a nearby frame, of a spectral parameter associated with a different frequency band. The resulting parameter indicates the extent to which the frequency of energy in the part of the spectrum represented by the given parameter is going up or going down. Energy difference parameters are calculated as a function of the difference between a given spectral parameter in one frame and a spectral parameter in a nearby frame representing the same frequency band.

2013028, Oct 31, 2013

Apr 26, 2012

13/456959

Michael Jack Newman - Somerville MA, US
Robert Roth - Newton MA, US
William D. Alexander - Lexington MA, US
Paul van Mulbregt - Wayland MA, US

G10L 15/04, G10L 11/00

704254, 704275, 704E11001, 704E15005

Techniques disclosed herein include systems and methods that enable a voice trigger that wakes-up an electronic device or causes the device to make additional voice commands active, without manual initiation of voice command functionality. In addition, such a voice trigger is dynamically programmable or customizable. A speaker can program or designate a particular phrase as the voice trigger. In general, techniques herein execute a voice-activated wake-up system that operates on a digital signal processor (DSP) or other low-power, secondary processing unit of an electronic device instead of running on a central processing unit (CPU). A speech recognition manager runs two speech recognition systems on an electronic device. The CPU dynamically creates a compact speech system for the DSP. Such a compact system can be continuously run during a standby mode, without quickly exhausting a battery supply.

6912498, Jun 28, 2005

May 2, 2001

09/845769

Daniell Stevens - Somerville MA, US
Robert Roth - Newtonville MA, US
Joel M. Gould - Winchester MA, US
Michael J. Newman - Somerville MA, US
Dean Sturtevant - Waltham MA, US
Charles E. Ingold - Bedford MA, US
David Abrahams - Cambridge MA, US
Allan Gold - Acton MA, US

ScanSoft, Inc. - Peabody MA

G10L015/04

704235, 704251, 704256, 704244

Correcting incorrect text associated with recognition errors in computer-implemented speech recognition includes receiving a selection of a word from a recognized utterance. The selection indicates a bound of a portion of the recognized utterance to be corrected. A first recognition correction is produced based on a comparison between a first alternative transcript and the recognized utterance. A second recognition correction is produced based on a comparison between a second alternative transcript and the recognized utterance. The duration of the first recognition correction differs from the duration of the second recognition correction. A portion of the recognition result that is replaced with one of the first recognition correction and the second recognition correction. includes at one bound a word indicated by the selection and extends for the duration of the one of the first recognition correction and the second recognition correction with which the portion is replaced.

7315818, Jan 1, 2008

May 11, 2005

11/126271

Daniell Stevens - Somerville MA, US
Robert Roth - Newtonville MA, US
Joel M. Gould - Winchester MA, US
Michael J. Newman - Somerville MA, US
Dean Sturtevant - Waltham MA, US
Charles E. Ingold - Bedford MA, US
David Abrahams - Cambridge MA, US
Allan Gold - Acton MA, US

Nuance Communications, Inc. - Burlington MA

G10L 15/26

704235, 704260, 704258, 704256, 704251

New techniques and systems may be implemented to improve error correction in speech recognition. These new techniques and systems may be implemented to correct errors in speech recognition systems may be used in a standard desktop environment, in a mobile environment, or in any other type of environment that can receive and/or present recognized speech.

6064959, May 16, 2000

Mar 28, 1997

8/825534

Jonathan Hood Young - Newtonville MA
David Wilsberg Parmenter - Newton MA
Robert Roth - Newtonville MA
Joev Dubach - Watertown MA
Gregory J. Gadbois - Amesbury MA
Stijn Van Even - Jamaica Plain MA

Dragon Systems, Inc. - Newton MA

G10L 1522, G10L 1526

704251

Incorrect text associated with recognition errors in computer-implemented speech recognition is corrected by performing speech recognition on an utterance to produce a recognition result for the utterance. When a correction command is identified in the recognition result for the utterance, corrected text is produced from a portion of the recognition result for the utterance.

6167377, Dec 26, 2000

Mar 28, 1997

8/825535

Laurence S. Gillick - Newton MA
Joel M. Gould - Winchester MA
Robert Roth - Newtonville MA
Paul A. van Mulbregt - Wayland MA
Michael D. Bibeault - Dracut MA

Dragon Systems, Inc. - Newton MA

G10L 1506, G10L 1508

704240

Language model results are combined according to a combination expression to produce combined language model results for a set of candidates. A candidate is selected and the combination expression is adjusted using language model results associated with the selected candidate.

5526463, Jun 11, 1996

Apr 9, 1993

8/045991

Laurence S. Gillick - Newton MA
Robert S. Roth - Newtonville MA

Dragon Systems, Inc. - Newton MA

G10L 900

395 26

The system of the invention relates to continuous speech pre-filtering systems for use in discrete and continuous speech recognition computer systems. The speech to be recognized is converted from utterances to frame data sets, which frame data sets are smoothed to generate a smooth frame model over a predetermined number of frames. A resident vocabulary is stored within the computer as clusters of word models which are acoustically similar over a succession of frame periods. A cluster score is generated by the system, which score includes the likelihood of the smooth frames evaluated using a probability model for the cluster against which the smooth frame model is being compared. Cluster sets having cluster scores below a predetermined acoustic threshold are removed from further consideration. The remaining cluster sets are unpacked for determination of a word score for each unpacked word. These word scores are used to identify those words which are above a second predetermined threshold to define a word list which is sent to a recognizer for a more lengthy word match.

7676367, Mar 9, 2010

Feb 20, 2004

10/783518

Robert Roth - Newton MA, US
Arkady Khasin - Acton MA, US
Laurence S. Gillick - Newton MA, US

Voice Signal Technologies, Inc. - Woburn MA

G10L 15/04, G10L 15/00

704252, 704251, 704231

A method of constructing a list of alternate transcripts from a recognized transcript includes generating a list of close call records, matching partial sub-histories from the recognized transcript with one of the history pairs stored in each of the records, and substituting the other of the history pairs for the partial sub-history of the recognized transcript. A close call record is generated each time a pair of partial hypotheses attempt to seed a common word. Each close call record includes history information and scoring information associated with a particular pair of partial hypotheses seeding a common word. Alternate transcripts are constructed by substituting close call histories for partial histories of the recognized transcripts, and also by substituting close call histories for partial histories of other alternate transcript.